A Voronoi diagram approach for detecting defects in 3D printed fiber-reinforced polymers from microscope images
作者机构：University of California BerkeleyBerkeleyCalifornia94720USA
出 版 物：《Computational Visual Media》 (计算可视媒体（英文版）)
年 卷 期：2023年第9卷第1期
页 面：41-56页
核心收录：
学科分类：08[工学] 080203[工学-机械设计及理论] 0802[工学-机械工程]
基 金：Arevo Inc Hanyang University, HYU
主 题：3D printing(3DP) microscope image processing fiber-reinforced polymer(FRP) Voronoi diagrams -shapes resin-rich areas
摘 要：Fiber-reinforced polymer(FRP)composites are increasingly popular due to their superior strength to weight *** contrast to significant recent advances in automating the FRP manufacturing process via 3D printing,quality inspection and defect detection remain largely manual and *** this paper,we propose a new approach to automatically detect,from microscope images,one of the major defects in 3D printed FRP parts:fiber-deficient areas(or equivalently,resin-rich areas).From cross-sectional microscope images,we detect the locations and sizes of fibers,construct their Voronoi diagram,and employ-shape theory to determine fiber-deficient *** Voronoi diagram and-shape construction algorithms are specialized to exploit typical characteristics of 3D printed FRP parts,giving significant efficiency *** algorithms robustly handle real-world inputs containing hundreds of thousands of fiber cross-sections,whether in general or non-general position.
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